Posts in category Costa Rica

Robalino-et-al-Park-Spillovers-LACEEP-WP78.Spillovers can significantly reduce or enhance the effects of land-use policies, yet there exists little rigorous evidence concerning their magnitudes. We examine how national parks within Costa Rica affect the clearing of forest nearby. We find that average deforestation spillover impacts are not significant within 0-5km and 5-10km rings around parks. However, we argue that this average blends multiple spillover effects, each of which is likely to vary in magnitude across the landscape, yielding varied net effects. We distinguish these effects using distances to roads and park entrances, given the importance of transport costs and, for Costa Rica, tourism. We find large and statistically significant leakage close to roads in areas without tourism, i.e., far from the park entrances. In contrast, no leakage is found far from roads or close to park entrances. In sum, the combination of low transport costs and low returns to forest is conducive to deforestation leakage around the parks.

Incentives conditioned on socially desired acts such as donating blood, departing conflict or mitigating climate change have increased in popularity. Many incentives are targeted, excluding some of the potential participants based upon characteristics or prior actions. We hypothesize that pro-sociality is reduced by exclusion, in of itself (i.e., fixing prices and income), and that the rationale for exclusion influences such ‘behavioral spillovers’. To test this, we use a laboratory experiment to study the effects of a subsidy to donations when participants are fully informed about why they are selected, or not, for the subsidy. We study the effects of introducing different selection rules upon changes in donations. Selecting for the subsidy those who initially acted less pro-social (i.e., gave little to start) increased donations, while random subsidies and rewarding greater pro-sociality did not. Yet a selection rule which targets lower prior pro-sociality also intentionally excludes the people who donated more initially, and only that rule reduced donations by the excluded. This shows a tradeoff between losses from excluded participants and gains from selected.

When designing schemes such as conditional cash transfers or payments for ecosystem services, the choice of whom to select and whom to exclude is critical. We incentivize and measure actual contributions to an environmental public good to ascertain whether being excluded from a rebate can affect contributions and, if so, whether the rationale for exclusion influences such effects. Treatments, i.e., three rules that determine who is selected and excluded, are randomly assigned. Two of the rules base exclusion on subjects’ initial contributions. The third is based upon location and the rationales are always explained. The rule that targets the rebate to low initial contributors, who have more potential to raise contributions, is the only rule that raised contributions by those selected. Yet by design, that same rule excludes the subjects who contributed the most initially. They respond by reducing their contributions even though their income and prices are unchanged.

We estimate the effects on deforestation that have resulted from policy interactions between parks and payments and between park buffers and payments in Costa Rica between 2000 and 2005. We show that the characteristics of the areas where protected and unprotected lands are located differ significantly. Additionally, we find that land characteristics of each of the policies and of the places where they interact also differ significantly. To adequately estimate the effects of the policies and their interactions, we use matching methods. Matching is implemented not only to define adequate control groups, as in previous research, but also to define those groups of locations under the influence of policies that are comparable to each other. We find that it is more effective to locate parks and payments away from each other, rather than in the same location or near each other. The high levels of enforcement inside both parks and lands with payments, and the presence of conservation spillovers that reduce deforestation near parks, significantly reduce the potential impact of combining these two policies.

We offer a nationwide analysis of the initial years of Costa Rica’s PSA program, which pioneered environmental-services payments and inspired similar initiatives. Our estimates of this program’s impact on deforestation, between 1997 and 2000, range from zero to one-fifth of 1% per year (i.e., deforestation is avoided on, at most, 2 out of every 1,000 enrolled hectares). The main explanation for such a low impact is an already low national deforestation rate. We also consider the effect of enrollment. Predicted deforestation on enrolled versus nonenrolled hectares, and matching analyses suggest an enrollment bias toward lower clearing threat. Enrolling land facing higher threat could raise payments’ impact on deforestation.

We estimate neighbor interactions in deforestation in Costa Rica. To address simultaneity and the presence of spatially correlated unobservables, we measure for neighbors’ deforestation using the slopes of neighbors’ and neighbors’ neighbors’ parcels. We find that neighboring deforestation significantly raises the probability of deforestation. Policies for agricultural development or forest conservation in one area will affect deforestation rates in non-targeted neighboring areas. Correct estimation of the interaction reverses the naive estimate’s prediction of multiple equilibria.

in Costa Rica. The first years of implementation set the basis for what the programme has become. Important changes have been made since the beginning, such as the institution in charge of implementing the programme, parcels selection criteria, and new offices that were opened in different areas of the country with the objective of reducing application costs. Using 2003 as the starting point of when these changes took place, we discuss if they had a programme efficiency effect on reducing deforestation. We focus on forest conservation contracts because it is the most important category of the programme in terms of budget and amount of land enrolled. We use matching techniques, geographic information systems (GIS), characterize the areas where payments were implemented in each of the time periods using a long list of variables, and look for similar areas that did not receive payments. We find that, as other studies have found for this period (Robalino et al, 2008; Arriagada, 2008), the impacts are low but significant. While it seems that, overall, institutional changes have not had a significant effect on impact, we also look at the impacts of forest conservation contracts per office. We find that those offices located in areas with high deforestation tend to have higher impacts.

To support conservation planning, we ask whether a park’s impact on deforestation rates varies with observable land characteristics that planners could use to prioritize sites. Using matching methods to address bias from non-random location, we find deforestation impacts vary greatly due to park lands’ characteristics. Avoided deforestation is greater if parks are closer to the capital city, in sites closer to national roads, and on lower slopes. In allocating scarce conservation resources, policy makers may consider many factors such as the ecosystem services provided by a site and the costs of acquiring the site. Pfaff and Sanchez 2004 claim impact can rise with a focus upon threatened land, all else equal. We provide empirical support in the context of Costa Rica’s renowned park system. This insight, alongside information on eco-services and land costs, should guide investments.

This chapter conveys why human choices complicate correct evaluations of impacts. Unobservable land choices, choices affecting policy location and interactions among choices complicate both ex post impact evaluation and ex ante policy planning. Based on application of proper methods to Costa Rica, we then suggest how these hurdles can best be addressed. We provide examples of: how a best practice deforestation baseline rightly conveys the constraints on the impact the pioneering Costa Rican eco-payments programme could have; why it may be critical to have different baselines for different locations to correctly infer the impacts of Costa Rican protected areas; and how choices by conservation agencies and landowners can determine the bias within heretofore typical approaches to impact evaluation.

Global efforts to reduce tropical deforestation rely heavily on the establishment of protected areas. Measuring the effectiveness of these areas is difficult because the amount of deforestation that would have occurred in the absence of legal protection cannot be directly observed. Conventional methods of evaluating the effectiveness of protected areas can be biased because protection is not randomly assigned and because protection can induce deforestation spillovers (displacement) to neighboring forests. We demonstrate that estimates of effectiveness can be substantially improved by controlling for biases along dimensions that are observable, measuring spatial spillovers, and testing the sensitivity of estimates to potential hidden biases. We apply matching methods to evaluate the impact on deforestation of Costa Rica’s renowned protected-area system between 1960 and 1997. We find that protection reduced deforestation: approximately 10% of the protected forests would have been deforested had they not been protected. Conventional approaches to evaluating conservation impact, which fail to control for observable covariates correlated with both protection and deforestation, substantially overestimate avoided deforestation (by over 65%, based on our estimates). We also find that deforestation spillovers from protected to unprotected forests are negligible. Our conclusions are robust to potential hidden bias, as well as to changes in modeling assumptions. Our results show that, with appropriate empirical methods, conservation scientists and policy makers can better understand the relationships between human and natural systems and can use this to guide their attempts to protect critical ecosystem services.

Economics of poverty, environment and natural resource use (chapter 6).

We review many theoretical predictions that link poverty to deforestation and then examine poverty’s net impact empirically using multiple observations of all of Costa Rica after 1960. Countrywide disaggregate (district-level) data facilitate analysis of both poverty’s location and its impact on forest. If the characteristics of the places the poor live are not controlled for, then poverty’s impact is confounded with differences between poorer and less poor areas and we find no significant effect of poverty. Using our data over space and time to control for effects of locations’ differing characteristics, we find that the poorer are on land whose relative quality discourages forest clearing, such that with these controls the poorer areas are cleared more. The latter result suggests that poverty reduction aids the forest. For the poorest areas, this result is weaker but another effect is found: deforestation responds less to productivity, i.e., the poorest have less ability to expand or to reduce given land quality.

We evaluated the intention, implementation, and impact of Costa Rica’s program of payments for environmental services (PSA), which was established in the late 1990s. Payments are given to private landowners who own land in forest areas in recognition of the ecosystem services their land provides. To characterize the distribution of PSA in Costa Rica, we combined remote sensing with geographic information system databases and then used econometrics to explore the impacts of payments on deforestation. Payments were distributed broadly across ecological and socioeconomic gradients, but the 1997–2000 deforestation rate was not significantly lower in areas that received payments. Other successful Costa Rican conservation policies, including those prior to the PSA program, may explain the current reduction in deforestation rates. The PSA program is a major advance in the global institutionalization of ecosystem investments because few, if any, other countries have such a conservation history and because much can be learned from Costa Rica’s experiences.

We review claims linking both payments for carbon and poverty to deforestation. We examine these effects empirically for Costa Rica during the late 20th century using an econometric approach that addresses the irreversibilities in deforestation. We find significant effects of the relative returns to forest on deforestation rates. Thus, carbon payments would induce conservation and also carbon sequestration, and if land users were poor could conserve forest while addressing rural poverty. We note that the poor appear to be marginalized in the sense of living where land profitability is lower. Those areas also have more forest. We find that poorer areas may have a higher supply response to payments, but even without this effect poor areas might be included and benefit more due to higher (per capita) forest area. They might be included less due to transactions costs, though. Unless the Clean Development Mechanism of the Kyoto Protocol is modified in its implementation to allow credits from avoided deforestation, such benefits are likely to be limited.

Even a perfect measure of the ecosystem services provided by each parcel enrolled in a PES program would be insufficient to measure the overall effectiveness of the program. The simple reason is that if a PES program does not lead to an increase in the provision of ecosystem services compared to what would have happened in the absence of the program—that is, the baseline or “counterfactual”—then it has not accomplished anything. Imagine a PES program focused on forest conservation that makes payments to managers of ecologically rich forest land, who have no incentive to clear the land because it is illsuited for logging, agriculture, or urbanization. Payments to these managers would have little impact on deforestation because the risk of clearing was minimal to begin with. In contrast, payments to managers who have incentives to clear their land would be much more likely to have an impact.

This chapter is structured as follows. Section 2 describes a simple model of interactions in the context of deforestation, based on an equilibrium in beliefs about the neighbours’ actions. Section 3 discusses empirical issues in measurement of interactions and the benefits of using an instrumental variable approach. Data requirements for analysing neighbours’ interactions in deforestation decisions are discussed in section 4. Finally, results for two regions within Costa Rica, as well as discussion of how to obtain the equilibria once the parameters of the model are estimated, are presented in section 5.

An index of ‘deforestation pressure’ is suggested as useful for reserve planning alongside the currently used information on the species present at candidate sites. For any location, the index value is correlated with threats to habitat and thus also survival probabilities over time for members of species dependent on that habitat. Threats in the absence of reserves are key information for planning new reserves. The index is estimated using a regression approach derived from a dynamic, micro-economic model of land use, with data on observed clearing of forest over space and time as well as biophysical and socioeconomic factors in land returns. Applying an estimated threat (or probability of clearing) function for Costa Rica to locations of interest yields relevant estimates of sites’ deforestation pressure, which are used to evaluate proposed reserves and to suggest other candidate sites.

The transformation and degradation of tropical forest is thought to be the primary driving force in the loss of biodiversity worldwide. Developing countries are trying to counter act this massive lost of biodiversity by implementing national parks and biological reserves. Costa Rica is no exception to this rule. National development strategies in Costa Rica, since the early 1970s, have involved the creation of several National Parks and Biological Reserves. This has led to monitoring the integrity of and interactions between these protected areas. Key questions include: ‘‘Are these areas’ boundaries respected?’’; ‘‘Do they create a functioning network?’’; and ‘‘Are they effective conservation tools?’’. This paper quantifies deforestation and secondary growth trends within and around protected areas between 1960 and 1997. We find that inside of national parks and biological reserves, deforestation rates were negligible. For areas outside of National Parks and Biological reserves we report that for 1-km buffer zones around such protected areas, there is a net forest gain for the 1987/1997 time period. Thus, it appears that to this point the boundaries of protected areas are respected. However, in the 10-km buffer zones we find significant forest loss for all study periods. This suggests that increasing isolation of protected areas may prevent them from functioning as an effective network.

Policy enabling tropical forests to approach their potential contribution to global-climate-change mitigation requires forecasts of land use and carbon storage on a large scale over long periods. In this paper, we present an integrated modeling methodology that addresses these needs. We model the dynamics of the human land-use system and of C pools contained in each ecosystem, as well as their interactions. The model is national scale, and is currently applied in a preliminary way to Costa Rica using data spanning a period of over 50 years. It combines an ecological process model, parameterized using field and other data, with an economic model, estimated using historical data to ensure a close link to actual behavior. These two models are linked so that ecological conditions affect land-use choices and vice versa. The integrated model predicts land use and its consequences for C storage for policy scenarios. These predictions can be used to create baselines, reward sequestration, and estimate the value in both environmental and economic terms of including C sequestration in tropical forests as part of the efforts to mitigate global climate change. The model can also be used to assess the benefits from costly activities to increase accuracy and thus reduce errors and their societal costs.

In this chapter we consider potential gains derived from preventing deforestation, drawing heavily from information from Chapter 14. It uses the same economic model and econometric technique and the same land use/land cover data. It also uses the carbon stock estimates presented there. The key difference is that, instead of using proxies for land-use returns such as ecological characteristics related to higher productivity, we attempt to directly estimate dollar-valued returns. We use these as an independent variable to explain and predict deforestation patterns. This allows us to simulate the potential supply of carbon sequestration in response to dollar-valued returns for certified emissions reductions. Payments for CERs will reduce deforestation by lowering the net return from forest clearing. The loss of the reward for carbon sequestration will partially offset the positive return from agricultural uses. To estimate the effect of such payments on deforestation, and hence CER supply, we need to estimate the response of deforestation to changes in returns to land use. An increase in agricultural returns is empirically equivalent to a reduction in carbon CER payments. Thus, we construct a variable that estimates the potential return of a plot of land if it is cleared. We construct a variable that varies across space (different crop suitability and yields) and time (changes in export prices, technology, and labor costs). We then use this variable in our econometric estimation. The results are used to calculate a supply curve of CERs. These results are illustrative only. They are produced as part of an ongoing effort at estimation (Kerr, Pfaff, Hughes et al. 2000) and are used to show some underlying features of a dynamic supply curve.

The chapter is structured as follows. First, below, we begin this analysis of the process influencing land changes with a dynamic model of land-use choices. Such models have often been suggested, but crucial features have often been neglected in application. This model generates testable hypotheses regarding factors underlying patterns of land-use changes in tropical areas. The next section describes the data collected for this project and discusses the quality of land-use data. It also outlines the variables used to test the implications of the model. Following that, we present our results and then discuss the linkage from land-use changes to implied carbon sequestration, and the quality of information currently available on carbon sequestration. Finally, we present some conclusions and lessons learned.

Protecting tropical forests under the Clean Development Mechanism (CDM) could reduce the cost of emissions limitations set in Kyoto. However, while society must soon decide whether or not to use tropical forest-based offsets, evidence regarding tropical carbon sinks is sparse. This paper presents a general method for constructing an integrated model (based on detailed historical, remote sensing and field data) that can produce land-use and carbon baselines, predict carbon sequestration supply to a carbon-offsets market and also help to evaluate optimal market rules. Creating such integrated models requires close collaboration between social and natural scientists. Our project combines varied disciplinary expertise (in economics, ecology and geography) with local knowledge in order to create high-quality, empirically grounded, integrated models for Costa Rica.